EXPERT SYSTEM FOR DECISION- MAKING BASED ON FUZZY LOGIC AND ANALYTIC HIERARCHY PROCESS TO ADVERSE WEATHER

Abstract

ABSTRACT: The volume of information used in the Emergency Coordination Center (1-1-2 CECOES), which depends on the Canary Government, during and after any adverse weather phenomenon (FMA in Spanish) is now significantly greater than before, The amount of bulletins warnings and forecasts about FMA sent by the Meteorological Agency (AEMET), and received at the 1-1-2 CECOES, is really considerable. The information should be treated as soon as possible in order to generate the corresponding pre-alerts and notifications, as well as public notices to the citizens The rule-based expert systems can overcome the human capacity, for example, when required to analyze a large volume of data in a limited period of time, as in the emergency services. Moreover, Fuzzy Logic is an artificial intelligence methodology that is effective when dealing with vagueness or ambiguity, erroneous or absence of information, something that the emergency services are used to: for example, "It rains a lot", "the storm is far away", " it is windy" and "we have low temperatures" , are typical responses given by some callers when they alert 1-1-2. Finally, Weather Forecasts usually work with imprecise concepts such as: possibility, (when the probability that a weather phenomenon occurs is between 10 and 40%) and probability, (when between 40 and 70%). We have primarily developed an expert helping-system for decision-making based on an inference engine implemented with Fuzzy Logic in CECOES 1-1-2. This system is able to provide clear answers at the inaccuracy or lack of information, and if trained with real cases, it can improve human behaviour giving a quick and effective response. Keywords: CECOES 1-1-2, Adverse Weather Phenomena, Expert System, Artificial Intelligence, Fuzzy Logic, Analytic Hierarchy Process (AHP).